Staff-Customer Experience

Job Description: Staff Customer Experience

Division: Market Research

Job Summary:

Responsible for executing end-to-end quantitative CX research, advanced data extraction, and AI-assisted analytics to generate actionable insights into customer needs, behaviors, and expectations across IOH’s products and services. The role supports management and cross-functional teams in improving NPS/CSAT, customer retention, and overall customer experience.

Key Responsibilities

1. Quantitative Research Design, Execution & Workflow

• Design and implement quantitative research methodologies based on business needs, including NPS/CSAT tracking, churn prediction studies, and large-scale consumer research.
• Develop research instruments, including structured questionnaires and measurement frameworks, to ensure reliable and actionable data.
• Support end-to-end research execution, either internally or in collaboration with external research agencies and vendors, from sample preparation through data collection.
• Develop and streamline survey and data collection workflows to improve research efficiency, scalability, and turnaround time.

2. Database Querying, Data Analytics & AI-Powered Insight Generation

• Extract, clean, and manipulate large quantitative datasets directly from cloud databases and data warehouses (e.g., Google Cloud Platform / GCP) using structured querying (SQL) to support research needs and baseline tracking.
• Track, monitor, and analyze key CX performance indicators, including Net Promoter Score (NPS), Customer Satisfaction (CSAT), and Customer Effort Score (CES), to identify trends and structural areas for improvement.
• Conduct unified analytics on structured and unstructured customer feedback using quantitative frameworks across multiple touchpoints (myIM3, bima+, call centers, retail outlets, social media) integrated into automated dashboards.
• Utilize agentic AI frameworks and LLM-driven research tools to accelerate quantitative data synthesis, automated sentiment classification, pattern recognition, and trend identification.
• Translate complex quantitative datasets into clear data storytelling and actionable strategic insights for key stakeholders.

3. Reporting & Stakeholder Management

• Prepare periodic quantitative research reports (weekly, monthly, and project-based), supported by live CX monitoring dashboards and GCP-backed data pipelines.
• Present quantitative research findings, analytical insights, and data-driven recommendations to management and product owners in a clear and structured manner.

Qualifications & Requirements

Educational Background & Experience:

• Education: Minimum Bachelor’s Degree (S1) in Statistics, Mathematics, Information Systems, Computer Science, Data Science, or a related quantitative field.
• Work Experience: 1–3 years of experience in Quantitative Market Research, CX Research, Consumer Insights, or Data Analytics. Experience in telecommunications or tech/digital sectors is a strong plus.

Technical & Analytics Skills:

• Database & Querying: Hands-on experience with cloud data platforms (e.g., Google Cloud Platform / GCP, BigQuery) and proficiency in writing queries (SQL) for data extraction, joining complex datasets, and processing raw analytics data.
• CX Frameworks: Strong foundation in quantitative CX metrics and frameworks (NPS, CSAT, CES, quantitative Customer Journey Mapping).
• Data Analytics & Visualization: Proficiency in data analysis tools and visualization platforms (e.g., Python, R, Tableau, PowerBI, or Looker).
• Research Automation & Agentic AI: Hands-on experience or working familiarity with AI tools and Agentic AI concepts (e.g., leveraging LLMs, AI research agents, or automated text/sentiment analysis tools for quantitative data synthesis).

Key Competencies & Soft Skills:

• Customer-Centric Mindset: Strong passion for understanding customer perspectives and utilizing empirical data to drive experience improvements.
• Data-Driven & Quantitative Thinking: Ability to analyze complex numerical data and construct logical, actionable business narratives.
• Adaptability to Emerging Technology: Proactive in learning and applying cloud technologies, advanced querying techniques, AI frameworks, and automated methodologies.
• Communication & Presentation: Fluent in English and Indonesian, with an ability to translate complex technical/quantitative findings into clear executive insights.
• Teamwork & Collaboration: Ability to work effectively with cross-functional technical (data engineers, IT) and business stakeholders to support strategic research objectives.